Update README.md

README.md

@@ -36,9 +36,8 @@ The core models released in this batch are the following:
 
 - **Project Page:**
 - **Repositories:** 
-    - Core repo (training, inference, fine-tuning etc.): colab examples cpt ,sft , orpo
-    - Evaluation code: github repo
-    - Further fine-tuning code: 
+    - Training: 
+    - Evaluation code: 
 - **Technical blog post:** 
 <!-- - **Press release:** TODO -->
 
@@ -154,7 +153,7 @@ GRAG-PHI-SFT, running on NVIDIA A100 with 8 GPUs for 5 days, has an approximate
 
 It's important to note that the actual power consumption may vary depending on the specific workload and operational conditions. For accurate power consumption measurements, using dedicated power monitoring tools is recommended.
 
-|           | GPU Type   | Power Consumption From GPUs | Carbon Intensity (kg CO₂e/KWh) | Carbon Emissions (tCO₂eq) |
+|           | GPU Type   | Power Consumption From GPUs | 
 |-----------|------------|-----------------------------|--------------------------------|---------------------------|
 | GRAG-PHI-SFT  | A100 ([Hessen AI supercomputer](https://hessian.ai/de/)   |  0.288 MWh                    |                           |                       |                    |